Simple inexpensive vertex and edge invariants distinguishing dataset strongly regular graphs
Jarek Duda
TL;DR
The paper tackles the graph isomorphism problem for strongly regular graphs by introducing inexpensive polynomial-time invariants that operate directly on the original graphs. It develops vertex invariants from neighborhood-restricted powers of the adjacency matrix $A$ via $\tilde{A}$ and edge invariants from edge-pair matrices $\bar{A}$, using traces (and in some cases sorted diagonals) of powers to obtain rotation-invariant discriminants. On Edward Spence's SRG dataset of $v$-vertex graphs, the vertex invariants distinguish all but 4 graph pairs, with the remaining pairs separated by the edge invariants, demonstrating strong empirical performance in a notoriously hard GI class. The results hint at a potential polynomial-time approach to GI for SRGs and motivate further work toward formal completeness proofs and broader applicability to other graph families.
Abstract
While standard Weisfeiler-Leman vertex labels are not able to distinguish even vertices of regular graphs, there is proposed and tested family of inexpensive polynomial time vertex and edge invariants, distinguishing much more difficult SRGs (strongly regular graphs), also often their vertices. Among 43717 SRGs from dataset by Edward Spence, proposed vertex invariants alone were able to distinguish all but 4 pairs of graphs, which were easily distinguished by further application of proposed edge invariants. Specifically, proposed vertex invariants are traces or sorted diagonals of $(A|_{N_a})^p$ adjacency matrix $A$ restricted to $N_a$ neighborhood of vertex $a$, already for $p=3$ distinguishing all SRGs from 6 out of 13 sets in this dataset, 8 if adding $p=4$. Proposed edge invariants are analogously traces or diagonals of powers of $\bar{A}_{ab,cd}=A_{ab} A_{ac} A_{bd}$, nonzero for $(a,b)$ being edges. As SRGs are considered the most difficult cases for graph isomorphism problem, such algebraic-combinatorial invariants bring hope that this problem is polynomial time.
